Sleep and Environment Control Method and System

ABSTRACT

A sleep system includes sensors capable of gathering sleep data from a person and environmental data during a sleep by the person. A processor executes instructions that analyze this data and control the sleep of the person and the environment surrounding the person. Typically, the instructions are loaded in a memory where they execute to generate an objective measure of sleep quality from the sleep data from the person and gather environmental data during the sleep by the person. Upon execution, the instructions receive a subjective measure of sleep quality from the person after the sleep, create a sleep quality index from the objective measure of sleep quality and subjective measure of sleep quality, correlate the sleep quality index and a current sleep system settings with a historical sleep quality index and corresponding historical sleep system settings. The instructions then may modify the current set of sleep system settings depending on the correlation between the sleep quality index and the historic sleep quality index. These sleep system settings control and potentially change one or more different elements of an environment associated with the sleep system.

CROSS REFERENCE TO RELATED PROVISIONAL APPLICATIONS

This application is related to and claims priority to U.S. applicationSer. No. 11/027,180 by Raphael Auphan filed Dec. 29, 2004 entitled Sleepand Environment Control Method and System and incorporated by referencein the entirety herein.

BACKGROUND

A great deal of research in recent years has been focused onunderstanding sleep and its physiological and psychological effect onhumans. While it is clear that humans require sleep to functionproperly, the qualities and quantities of sleep required is a much morecomplex problem. For example, some individuals that sleep too little mayfeel tired or fatigued during the day while other individuals that sleeptoo many hours have a similar feeling of grogginess as a result ofsleeping too much. Researchers continue to study many differentphysiological conditions during sleep to understand the complexinterplay between sleep and wakeful well-being.

To better analyze sleep, these researchers have broken sleep down into aframework or architecture having a series of cycles. One type of sleeparchitecture divides these cycles into REM (rapid eye movement) andNon-REM (NREM) types of sleep. A further classification divides the NREMsleep into: Stage 1 or Light Sleep—marked by a slowing in breathing andheart rate during the transition from waking and sleeping, Stage 2 orTrue Sleep—further identified with muscle relaxation, reduced or limitedeye movement as well as body movement, Stage 3 or Deep Sleep PhaseI—additional slowing of heart and breathing and Stage 4 or Deep SleepPhase II—this is the deepest stage of sleep and arousal can bedifficult. In contrast, REM stage or Dream Sleep is a separate type ofsleep marked by a more distinct reduction in muscle tone and no bodymovement however breathing and heart rate may increase and becomeirregular; during REM eye movements are rapid as a person has vividdreams.

Expensive computers and diagnostic equipment have been developed alongwith this research to identify these stages while a person sleeps. Sleepclinics located at hospitals and other medical research institutionsadmit patients briefly for one to two evenings for monitoring andanalysis in order to diagnose sleep related illnesses and conditionslike sleep apnea, insomnia, narcolepsy and other diseases. Medicaldoctors carefully review vital signs and other information collectedfrom the person during sleep in an attempt to diagnose the specificconditions having a deleterious effect on the person's health andwell-being. Due to the costs and business-like nature of medicine,doctors not only diagnose but often suggest medical procedures,prescription drugs and/or medical devices based on the data gatheredduring these abbreviated sessions. In minor cases, a doctor mayprescribe a sedative or other drug to alleviate stress and induce sleepwhile in the more severe cases the doctor may also recommend medicaldevices to address specific conditions (i.e., a mask and breathingapparatus for sleep apnea) and perform radical and painful surgeryinvolving the throat, nasal cavities, tongue and respiratory tract.

Drugs and surgical procedures not only represent risks but are oftenineffective at treating sleep disorders. This is not surprising giventhe limitations and imperfections in monitoring and treating sleepdisorders. First, the monitoring done in hospitals is expensive andtypically available only near large universities and researchinstitutions. As a result, data collected does not reflect across-section of society or a broad range of people but insteadrepresents only those people near the sleep clinics and/or withsufficient insurance and financial resources to pay for the work. Theresulting sleep data available is therefore limited and potentially toosmall to be considered statistically significant.

Further, data collected during these one or two night stays are oftentoo short and unpredictable to make accurate assessment of problem. Forexample, a person sleeping in a clinic with numerous monitoring devicesand other equipment may be uncomfortable and exhibit additional sleepproblems. Any information gathered over the short period of time in asleep clinic may reflect the person's discomfort sleeping in a clinicwith numerous monitors rather than displaying the symptoms of a truesleeping disorder (i.e., sleep apnea, narcolepsy, etc.)

Current sleep research also does not address the more subtle sleepproblems suffered by the majority of people as the focus has been moreof a last resort for people with severe sleep conditions. If it werepossible, many people could benefit from sleep research if it wereavailable more widely and inexpensively.

SUMMARY

One aspect of the invention includes a sleep modification method thatincludes gathering environmental data during a person's sleep and sleepdata from the person during the sleep wherein the sleep data is used togenerate an objective measure of sleep quality. After each sleep, themethod obtains a subjective measure of sleep quality from the personuseful in creating a sleep quality index from the objective measure ofsleep quality and subjective measure of sleep quality. A correlation isdrawn between the sleep quality index and a current set of sleep systemsettings with a historical sleep quality index and correspondinghistorical sleep system settings. Depending on the correlation, thecurrent set of sleep system settings are modified thus potentiallyaffecting the environment.

Another aspect of the present invention includes a system for sleepanalysis and modification that includes a set of sleep repositorydatabases accessible over a network and connected to one or morecomputer systems, a sleep trend analysis computer system capable ofanalyzing trends from the data on the set of sleep repository databasesand generating sleep quality indices and corresponding expected sleepsystem settings and a network that provides the expected sleep systemsettings to one or more sleep systems for one or more people dependingon each person's goals during sleep.

Yet another aspect of the present invention includes a sleep system anda set of sensors to gather sleep data from a person and environmentaldata during a sleep by the person from their environment. The sleep datais particularly useful in generating an objective measurement of sleepquality. The sleep system has a processor capable of executinginstructions to analyze and control the sleep of the person and theenvironment surrounding the person. During execution, a memory is loadedwith instructions to generate an objective measure of sleep quality fromthe sleep data from the person and obtain environmental data during thesleep by the person, receive a subjective measure of sleep quality fromthe person after the sleep, create a sleep quality index from theobjective measure of sleep quality and subjective measure of sleepquality, correlate the sleep quality index and a current set of sleepsystem settings with a historical sleep quality index and correspondinghistorical sleep system settings, modify the current set of sleep systemsettings depending on the correlation between the sleep quality indexand the historic sleep quality index. Depending on the correlation, thesleep system modifies the set of sleep system settings and a set ofcontrols capable of changing one or more different elements of anenvironment associated with the sleep system.

Other features and advantages of the invention will become apparent fromthe description, the drawings, and the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a network of sleep systems and servers for sleep analysisand modification in accordance with one implementation of the presentinvention;

FIG. 2 depicts components of a sleep system used for analysis andmodification of sleep in accordance with one implementation of thepresent invention;

FIG. 3 depicts a sleep system with sensors and controls integrated intoa bed in accordance with one implementation of the present invention;

FIG. 4 is another bed having a sleep system designed in accordance withthe present invention added afterwards rather than being integrated aspreviously described in conjunction with FIG. 3;

FIG. 5 is a flowchart diagram of the operations used to modify aperson's sleep in accordance with one implementation of the presentinvention; and

FIG. 6 depicts a set of alternate approaches to gather historical sleepdata, historical sleep quality indices and historical sleep systemsettings in accordance with one implementation of the present invention.

Like reference numbers and designations in the various drawings indicatelike elements.

DETAILED DESCRIPTION

Aspects of the present invention include a sleep system for monitoringsleep and controlling the environment where a person is sleeping.Numerous sensors built into the sleep system gather data from the personand the environment and then process the information to identify trendsand sleep quality for the individual. Historical sleep data for theperson is stored in a local repository and used during sleep analysis aswell as an optional global sleep repository with the sleep data for manyindividuals. Depending on the individual's goals, the sleep system isadjusted causing subtle changes in the environment (i.e., sound, light,heat/cooling, vibration etc.) to improve and meet these goals related tosleep and overall health.

While there are many different advantages not all of which arespecifically identified herein, one or more aspects of the presentinvention may include one or more of the following advantages. A sleepsystem and related processing can be implemented as easily in a person'shome as a clinical or hospital setting. The sleep system is designed tomonitor sleep patterns and sleep quality of a person without requiringexpertise or training in sleep analysis and diagnosis. Built in sensorsand feedback loops in the system monitor a person's body and environmentand then use sophisticated computer implemented data analysis routinesto modify the environment and improve the person's sleep. By collectingsleep data from the person in a local sleep repository over a period oftime, the sleep patterns for the person can be readily detected andaccommodated with customized stimulus most suited for the individual. Ifit is desired, the person can also connect to a global sleep repositoryand use sleep data from larger groups of individuals to help determineoptimal sleep settings for their particular sleep system and sleepcondition.

Multiple objective, subjective and environment factors are used incombination to evaluate a person's sleep. Sensor inputs recording vitalsigns of a person during sleep are combined with environmental sensorinformation to provide a context or baseline for the person's sleepanalysis. If environmental sensor information is not available ordesired then objective factors related to a person's vital signs canalternatively be used without the environmental information. Additionalfactoring in of subjective information gathered from each personconcerning their perceived condition before, during and after sleephelps tailor the analysis to each individual. These many differentfactors help facilitate a more accurate assessment and improvement of aperson's sleep.

Longer term data collection and sleep trend analysis is possible withimplementations of the present invention. Instead of being limited toone or two hours or nights in a sleep clinic or hospital, sleep systemsinstalled in a home setting can gather data over days, months or evenyears. False readings due to uncomfortable sleep situations ormonitoring devices can eventually be identified and factored out overtime. These additional data points describing a sleep condition over alonger period of time help customize the analysis and develop moreaccurate models of a person's sleep patterns and cycles. More can belearned about sleep over time as the sleep data is collected andcompared with larger populations of people.

FIG. 1 depicts a network of sleep systems and servers for sleep analysisand modification in accordance with one implementation of the presentinvention. System 100 includes sleep systems 102, 104, 106, 110 and 112coupled together over a network 114 such as the Internet. Additionally,system 100 also includes a clinical sleep analysis and monitoring system108 and sleep trend analysis server 124 both capable of accessing datastored in sleep data repository 116, environmental data repository 118,body data repository 120 and global sleep repository 122.

Sleep systems 102, 104, 106, 110 and 112 are designed to gather sleepand body data from individuals as they are sleeping as well asenvironmental data surrounding the sleep systems. For example, sleepsystem 102 gathers body and sleep related information and environmentaldata and stores in a local storage area to be accessed later during ananalysis phase. The body information typically includes vital signsmeasured directly from the person during the sleep cycle and includesthe time period before falling asleep as well as the time period whileasleep and the period following when the person wakes up. In addition tohaving a variety of sensors, the sleep system includes various computerprocessing devices and controls outputs for controlling the environment.Optionally, these various devices can be integrated into a bed and otherbedding or can be added to any existing bed or bedding as described infurther detail later herein.

Clinical sleep analysis and monitoring system 108, hereinafter clinicalmonitoring system 108, is an optional component available for use byeach sleep system user as an additional service. While implementationsof the present invention can readily work as a standalone device, insome cases, a person may desire that they need special assistancemonitoring and diagnosing their sleep. These people would pay accordingto a monthly, annual or other fee schedule for a qualified sleepspecialist, medical doctor or researcher to monitor and respond tocertain sleep conditions. If a person or system at clinical monitoringsystem 108 detects an issue with respect to a person's sleep then theywill contact the individual and notify them of the anomalous condition.In response, the personnel at the monitoring service can directly adjustthe environmental settings or modify the settings of the sleep systemover a remote link in order to improve the sleep quality of the person.Conversely, the person using one of the sleep systems may opt not to useclinical monitoring system 108 and instead rely on the analysis,modeling and trend analysis functions already built into the sleepsystem designed in accordance with the present invention.

Sleep trend analysis server 124 and various sleep repositories representyet another optional service available to each user of a sleep system.Instead of working with data related to a specific individual, sleeptrend analysis server 124 can perform analysis on large populations ofpeople using sleep systems of the present invention. Participating sleepsystems 102, 104, 106, 110 and 112 can opt-in to populate each of sleepdata repository 116, body data repository 120 and environmental datarepository 118 with information gathered over time. In exchange, theseparticipating sleep systems 102, 104, 106, 110 and 112 have access to awider range of information and sleep system setting suggestions andoptions other than from the individual local storage database.

The datasets associated with sleep data repository 116 includeinformation directly related to sleep quality. For example, sleeprelated information may include a number of wakeups during sleep time,duration of these wakeups during sleep time and other types of relatedinformation. Environmental data repository 118 stores details on theenvironment before, during and after sleep time while body datarepository 120 retains more specific information concerning vital signsand other details of the individual person as they sleep. Of course,these repositories are cross referenced using various indices and/or canbe combined into a single larger repository if so desired.

Global sleep repository 122 holds the results of trend analysisperformed by sleep trend analysis server 124 on these above mentionedrepositories (i.e., sleep data repository 116, body data repository 120and environmental data repository 118). One objective of the trendanalysis is to determine one or more optimal sleep system settings foreach of sleep systems 102, 104, 106, 110 and 112 under variouscircumstances. Due to the complexity of identifying an optimal solution,one or more techniques implemented by sleep trend analysis server 124relies upon various heuristics and solution methodologies for solvingother N-P complete problems including: genetic programming techniques,tree-based modeling solutions and artificial intelligence analysis. Asdescribed in further detail later herein, a sleep quality index andcorresponding set of sleep system settings generated by sleep trendanalysis server 124 are made available on demand to one or more of thesleep systems in network 100.

FIG. 2 depicts components of a sleep system used for analysis andmodification of sleep in accordance with one implementation of thepresent invention. As illustrated in this example, sleep system 200includes a processor 202, a network connection 204, a set of body andsleep monitoring sensors 206, environmental monitoring sensors 208, anenvironmental control interface 210, local storage 212 and memory 214.Alternate implementations of the present invention may include fewerthan all of these options as needed by the specific design. For example,a standalone sleep system 200 may not include network connection 204 ifcommunicating with other devices, sleep systems or data storage is notneeded.

Processor 202 can be one or more general purpose processors arranged toprocess instructions in parallel or in a cluster arrangement.Alternatively, processor 202 can also include a set of special purposeembedded processors designed to work together on specific processingtasks associated with sleep analysis and modification as needed byimplementations of the present invention. Network connection 204provides connectivity to an intranet or the Internet and access tolarger repositories or databases of sleep data and information aspreviously described. This network connection 204 can also be used todownload updates to applications or firmware within sleep system 200 aswell as provide the ability to provide remote monitoring and/or remotediagnostics on sleep system 200 and/or the person.

Body and sleep monitoring sensors 206 provide an interface and sensorsfor gathering vital signs and other information about the person as theyfall asleep, sleep and then wakeup. In one implementation, these bodyand sleep monitoring sensors 206 include a respiration sensor 218 tomeasure breathing rate and gas mixture (VO2 levels), heartbeat sensor220 to measure heart rate, heart rate variability and pulse, movementsensor 222 to measure body movement and various other miscellaneous bodysensors 224 useful in sleep analysis. To minimize the impact on sleep,these sensors should be designed to collect data non-invasively howeveralternate implementations of the present invention will also work withmore invasive devices that touch or are placed upon the person. Thesevarious sensors are fed into a signal processing component 226 to filterand digitize the various results and prepare for further analysis.

A different set of sensors in environmental monitoring sensors 208include: an air sensor 228 for measuring air temperature and quality, alight sensor 230 for measuring the intensity and frequency of the lightin the environment, a temperature sensor 232 that measures ambient roomtemperature and various other miscellaneous environmental sensors 234 asneeded by the sleep analysis performed in accordance with the aspects ofthe present invention. For example, one environmental sensor 234 couldinclude a sound sensor to detect and measure certain sound levels andfrequencies.

Environmental control interface 210 sends different control signals outdepending on sleep analysis results from the sensor data, historicaldata and other inputs as described later herein. These control signalscause various conditions in the environment to change with the desiredeffect being to influence and improve the sleeping quality of theindividual person sleeping or about to sleep in the particularenvironment. In one example implementation as illustrated, the controlsignals from environmental control interface are capable of interfacingand controlling one or more of the following environmental conditions:light 238 (intensity and color), temperature 240 (both temperature atsleep surface as well as surrounding areas), air 242 (volume, humidity,gas composition, scents and temperature) 242, sound 244 (volume,frequency and timbre), vibration 245 and many others 247. For example,environmental control interface can also interface with audio/videoequipment and devices for playing movies, music and sounds. In manycases, the desired environmental condition depends on the sleep cycle aperson is in (i.e., light sleep, deep sleep, REM/dream sleep) or goinginto and may need adjusting accordingly depending on their preferencesand particular sleep cycle architecture.

Local storage 212 is a dataset storage area for storing data collectedfrom the sensors, and data processed/analyzed by the system as well assubjective information collected from the person. As previouslydescribed, this information can be kept locally and/or can betransmitted to one or more global repositories to be stored along withsleep information from many other people. Historical sleep data 246includes raw and processed data describing the person's actual sleepcharacteristics over a period of time. In many cases, the historicalsleep data 246 is inferred directly from data taken from one or more ofthe various sensors. For example, the number of wakeups andcorresponding duration of wakeups can be determined based upon movementdata collected from movement sensor 222 in addition to other vital signstaken from the various other vital signs measurements. Historicalenvironment data 248 is also a collection of raw data taken over timeexcept it concerns environmental information obtained directly throughenvironmental monitoring sensors 208 as previously described.

Sleep analysis archive 250 is a collection of sleep analysis resultsperformed over time and kept for future reference. The sleep analysisresults in sleep analysis archive 250 are derived by identifying trendsin past data and information collected by the various sensors in sleepsystem 200 and through subjective feedback provided by the person aftera sleep.

Personal preferences 252 include preferred settings for each personusing sleep system 200. These preferences in personal preferences 252can be changed quickly to accommodate multiple people using sleep system200 without requiring reprogramming or retraining. For example, thepreferences can specify a modified and personal sleep architecture 254that has been modified to suit a particular user. Personal sleeparchitectures 254 describe classical stages of sleep tailored to eachindividual person. For example, a sleep architecture having stage 1(light sleep), stage 2 (true sleep), stage 3/4 (deep sleep) or deltasleep and REM stage (dream sleep) may also indicate more specific timeintervals for each depending on the historical analysis of sleep for theindividual. Additional preferences included in personal preferences 252can also include air temperature range settings not to exceed or heartrate and blood pressure threshold levels to set off warnings or otheremergency procedures.

A number of example components useful in sleep and sleep qualityanalysis are illustrated in memory 214 including: a sleep cycle analysiscomponent 256, a sleep quality correlation component 258, a sleepoptimization component 260, a sleep system interface component 260 and aruntime component 264 for managing the resources in memory 214 and otherparts of sleep system 200.

Sleep cycle analysis component 256 analyzes sensor information,environmental information and subjective information from the person andconstructs a more accurate sleep architecture for the individual. Thiscan involve adjusting the times associated with each cycle of the sleeparchitecture as well as drawing a correlation between the data from oneor more sensors and the particular person's entry or exit from thedifferent cycles. For example, sleep cycle analysis component 256 mayalso include analyzing the effectiveness of past wake-up times and thensetting a more optimal wake-up time based upon the persons and desiredwake-up time frame (i.e., if the desired wakeup period is between 6 amand 7 am, the system may analyze the sleep data gathered during thenight and determine that the most optimal wakeup time would be 6.15 am).

Once the sleep cycle architecture is known for each person, sleep cycleanalysis component 256 is also responsible for developing an objectivemeasure of sleep quality through analysis of the sensor data from theperson and, optionally, from the environment. Objective measures ofsleep quality in one implementation are based upon factors that include:sleep inertia after waking up, sleep debt accumulation, architecture ofsleep phases, breathing quality, sleep efficiency, duration of wakeupsduring sleep time, actual frequency of wakeups, sleep onset time,wake-up time, total sleeping time and actual time taken to fall asleep.If it is desired these objective factors related to the body and sleepof the person can also be combined with environmental sensor informationresults as previously described and collected via environmentalmonitoring sensors 208.

Sleep quality correlation component 258 combines an objective measure ofsleep quality with subjective measurements of sleep quality obtainedfrom the person and generates a sleep quality index. The sleep qualityindex is a weighted combination of the objective and subjective measuresof sleep quality. In some cases, the sleep quality index may also benormalized to allow a personal sleep quality index to be compared withthe sleep quality index of other people. Correlations are generally madeusing both current and historical sleep quality index values as theyrelate to sleep system settings. Depending on the type of analysis, itmay also be useful to combine environmental data in these correlationcalculations. Many times environmental factors have a noticeable effecton a person's sleep and therefore justify performing additionalcomputations and correlative analysis.

It is contemplated that the subjective factors are generally obtainedshortly after a person wakes up and are based primarily upon theperson's perception of the sleep. In some cases, these perceivedmeasures of quality may match the more objective measures taken throughsensors while in other cases they may not match up. In any event,implementations of the present invention consider and weight thesubjective factors in light of their consistency over time rather thanwhether they identically track or closely track other measures orresults taken using sensors. These subjective measures of sleep qualityinclude: body comfort, stress level on wakeup, stress level to sleep,perceived somnolence during day, recall of dreams, frequency of wakeupsrecalled, perceived time to fall asleep, overall perception at wake-upand overall perception of sleep quality.

In practice, a person using sleep system 200 might enter thesesubjective measures of sleep quality through a small remote controlhaving a touch screen and capable of scrolling various multiple choiceand other questions in front of the person after waking up. Sleep systeminterface component 262 would likely have a set of screens available forthe creation and procuring of subjective measures of sleep quality fromthe person. The results of these enquiries would be forwarded over awireless or wired connection to sleep system 200 for further analysisand consideration.

Additional functions performed through sleep system interface component262 can also include setting up personal preferences 252 and anyadditional alerts or alarms to be set upon reaching certain thresholdconditions (i.e., low oxygen intake, high blood pressure, slowed orstopped breathing etc.) One personal preference 252 can request sleepsystem 200 to identify certain sleep patterns and then suggest one ormore modifications to the person for improving sleep based on collectedsleep information and analysis. An expert system designed to analyzesleep patterns and make suggestions allows the user to take control ofcertain aspects of sleep system 200 without having to understand andanalyze all the details. For example, sleep system 200 may notifythrough sleep system interface component 262 a certain time during sleepwhen a person is restless and moving about. Using an expertknowledgebase of information on sleep, sleep system 200 also might thensuggest either a temperature increase, increased oxygen flow or someother intervention to address the specific condition. The person wouldbe able to select one of these responses to perform by sleep system 200as a preference next time the condition occurs. Of course, the personcan also override the expert system and directly instruct sleep system200 to operate in a certain manner upon occurrence of almost anydetectable event.

Sleep optimization decision component 260 and confidence basedarbitrator 266 work together in determining how to improve the person'ssleep experience. In one implementation, sleep optimization decisioncomponent 260 receives sleep analysis information from sleep cycleanalysis component 256 and sleep quality correlation component 258 anddetermines whether to adjust the settings of sleep system 200. In somecases, the basis for these decisions depends entirely on historicalsleep and environmental information stored in local storage 212 while inother cases additional historical sleep information is obtained fromother people and correlated with their corresponding sleep quality indexand sleep system settings. If the trend for changing the sleep systemsettings is clear then sleep optimization decision component 260 sendssignals over environmental control interface 210 as appropriate to alterthe environment.

However, if it is unclear what changes in sleep system 200 are needed orthere is a deadlock then confidence based arbitrator 266 acts as asecondary decision maker in the process. For example, analysis by sleepoptimization decision component 260 may result in a conflicting set ofinstructions to increase air temperature and simultaneously lower airtemperature. Confidence based arbitrator 266 would determine which ofthe decisions is more likely to be correct based on confidence basedfactors and then choose one decision over the other to break thedeadlock.

The organization of data in local storage 212 and the componentsdescribed above in memory 214 represents only one possible solution andit is contemplated that each of these datasets and components could becombined with other datasets or components or separated into a furtherlarger number of datasets or components depending on the designdecisions and choices made during implementation. Further, while thecomponents are illustrated in this example as appearing in main memoryof a device however they could also be loaded and run from local storage212 on a disk drive or removable memory/storage (not shown). Inaddition, data in local storage 212 and components in memory 214 couldinstead be mastered onto a DVD or CD-ROM. Accordingly, these componentsare illustrated in memory as one example approach to process theseinstructions.

FIG. 3 depicts a sleep system with sensors and controls integrated intoa bed in accordance with one implementation of the present invention.The sleep system 314 in this example is designed into and integratedwith a complete bed. Accordingly, bed system 300 includes a sensorpillow 302, sensor fitted bed sheet 304, overhead monitors 306,integrated air ducts 308 a-c, multimedia area 310, air processing unit312, sleep system 314 and sleep user control device 316.

Sensor pillow 302 and sensor fitted bed sheet 304 are used primarily toobtain various measurements from the person sleeping. These measurementstaken from the person are made through various sensors including, forexample, respiration sensors, heartbeat and blood pressure sensors, EEG(electroencephalogram) sensors, ECG/EKG (electrocardiogram) sensors,movement sensors and body temperature sensors. As measurements are madethey are immediately transmitted to sleep system 314 for storage andsubsequent or immediate processing.

Overhead monitors 306 include sensors used primarily in sampling theenvironment and determining, among other things, air temperature andquality, light intensity and frequency in the environment, ambient roomtemperature and various other environmental qualities as needed.Additionally, cameras, video cameras and infrared cameras can beincluded in overhead monitors to monitor the persons movements andbehavior during sleep. These measurements are also sent immediately tosleep system 314 for storage and processing.

Depending on the sleep cycle, one or more environmental controls inbed-system may be activated or altered. Integrated air ducts 308 a-c canbe adjusted to intake and exhaust air as needed to effectuate a moreimproved sleep condition for the person. For example, the air flow couldbe increased to either increase or decrease temperature as well aspotentially increase the level of oxygen in the sleeping area (e.g.,either by increasing the overall air flow or by actually increasing thepercentage of oxygen in the air mixture). Additional air ducts may alsobe included in multimedia area 310 as needed.

Positioned just over the eyes of the person sleeping, multimedia area310 includes lights, sound speakers and optionally an image producingscreen (i.e., LCD or plasma) to project certain soothing images orpatterns. Lights in multimedia area 310 can be controlled to permitreading before sleep or viewing of tranquil scenes or favoriteimages/patterns. Different patterns can be displayed and may havedifferent effects on the person depending on their experiences andviewpoints. For example, mountain scenery may provide a peaceful feelingfor some individuals or feelings of fear for people afraid of heights.

In this example, the air processing box unit 312 and sleep system 314are located just underneath the bed however it is also possible they arelocated at an additional distance from the person sleeping. For example,it may be desirable to have air processing unit 312 located remotely toreduce ambient noise levels and also provide additional storageopportunities in the bedroom or sleeping area. Similarly, sleep system314 can be located centrally to several rooms in a house to allow forthe monitoring and control of several bed-systems 300 at once.

Sleep control device 316 is used by the person sleeping to turn bedsystem 300 on and off as well as interface and program the system asneeded. As previously mentioned, sleep control device 316 can beequipped with a touch screen and may even include a small embedded webbrowser compatible with HTML/XML and other web based interfaceprogramming protocols. Alternatively, the person can operate sleepcontrol device 316 using the buttons and/or touch screen elements tothen browse one or several web pages displayed upon a display inmultimedia area 310.

FIG. 4 is another bed having a sleep system designed in accordance withthe present invention added afterwards rather than being integrated aspreviously described in FIG. 3. In this example, a bed 400 is modifiedby adding sensor pillow 402 and/or sensor fitted bed sheet 404 thatoperate as previously described with respect to similar sensors in bedsystem 300. Instead of overhead, a pair of side monitors 406 a-bincludes sensors that work together in sampling the environment anddetermining, among other things, air temperature and quality, lightintensity and frequency in the environment, ambient room temperature andvarious other miscellaneous environmental conditions as needed. Onceagain, these measurements are sent immediately to sleep system 414 forstorage and processing. Air intake and exhaust ducts 408 a-b and pair ofmultimedia areas 410 a-b are also located on the sides and operate in asimilar manner as the corresponding functional elements described withrespect to bed system 300 in FIG. 3. Likewise, air processing unit 412,sleep system 414 and sleep control device 416 have similar function andoperation as previously described in FIG. 3 as well. In this case, sleepcontrol device 416 has a screen to display information and a touchscreen to make selections unless an external screen/monitor (not shown)is plugged into sleep system 414 and used to guide the selection ofoptions and preferences.

FIG. 5 is a flowchart diagram of the operations used to modify aperson's sleep in accordance with one implementation of the presentinvention. Upon first use or initial use, a person may specify theirobjective characteristics and sleep goals to the sleep system (502). Theobjective characteristics may include sex, age, weight, relative fitnessand other information readily quantified by the person about to use thesleep system. Sleep goals can be provided by selecting one of several ormany options that may include: quicker time to fall asleep, deeper REMsleep, fewer wakeups during sleep, longer sleep times, more efficientsleeps or other types of sleep goals.

Next, the sleep system begins to gather environmental data during asleep by a person and sleep data from the person and to generate anobjective measure of sleep quality (504). Generally, the environmentaldata is not required to generate the objective measure of sleep butuseful in drawing correlations between the sleep data from the personand the environmental factors as they occur. In one implementation, theobjective measures of sleep quality include: sleep inertia after wakingup, sleep debt accumulation, architecture of sleep phases, breathingquality, sleep efficiency, duration of wakeups during sleep time, actualfrequency of wakeups, sleep onset time, wake-up time, total sleepingtime and actual time taken to fall asleep. While sleep inertia isconsidered an objective measure of sleep, it can be measured by askingthe person to perform a very basic test or skill to determine the levelof alertness after wakeup as direct measurement is more difficult. Ifthe person wakes up numerous times then the time taken to fall asleep ineach instance is also recorded and preferably minimized when it doesoccur. The typical time taken to fall asleep is measured from the timethe lights are out to the time the person experiences the onset ofsleep. Over time, the sleep system provides suggested times to fallasleep and may also run various light and sound programs to assist inthis process.

Once the person has awoken from sleep, the sleep system then enquiresfor a subjective measure of sleep quality (506). This measure of sleepquality is largely based upon the person's perception and helps thesleep system learn what type of sleep and settings in the sleep systemmakes the person feel more rested. Typically, the person enters thesesubjective factors through the sleep control unit and/or a visualgraphical user interface (GUI). The subjective factors providedgenerally concern overall body comfort, stress level on wakeup, stresslevel to sleep, perceived somnolence during day, recall of dreams,frequency of wakeups recalled, perceived time to fall asleep and overallperception of sleep quality. Sleep inertia is also considered asubjective factor and measured upon wakeup by asking the person abouttheir perceived sleep inertia or grogginess upon wakeup.

To account for both the objective and subjective measurements of sleepquality, the sleep system then creates a sleep quality index from theobjective measurement of sleep quality and subjective measurement ofsleep quality (508). In one implementation, this sleep quality index isa weighted combination of both the objective and subjective measurementsof sleep quality. It may be important to normalize this sleep qualityindex in order to compare the index and sleep system settings with theindices and sleep system settings of other people using the sleepsystem. For example, a sleep quality index (SQI) can be computed asfollows:

${{SQI} = {{W_{s} \cdot {\sum\limits_{{ST} = x}^{m}{{Subjective}\mspace{14mu} {Sleep}\mspace{14mu} {Quality}_{ST}}}} + {W_{o} \cdot {\sum\limits_{{OT} = y}^{n}{{Objective}\mspace{14mu} {Sleep}\mspace{14mu} {Quality}_{OT}}}}}}\mspace{14mu}$

Where:

W_(s) is weight attributed to subjective sleep quality factor

W_(o) is weight attributed to objective sleep quality factors

m is the number of subjective sleep quality samples

n is the number of objective sleep quality samples

x is the starting sample for subjective sleep quality measurement

y is the starting sample for the objective sleep quality measurement

The sampling for the subjective factors and objective factors isperformed at the highest rate possible to allow for many different typesof analysis. Generally, the sampling for the subjective sleep quality isperformed upon waking as it requires the person to be awake and provideinformation. For example, this sampling rate would typically be once aday in the morning when a person wakes up and the number of sampleswould therefore correspond to the number of days included in part of theanalysis. The subjective sleep quality for a one month period wouldnecessarily included 30 samples of subjective sleep quality whileanalysis for a 2 week period might only include 10-14 samples. Ofcourse, many more subjective sleep quality samples are also possible ifa person sleeps and wakes up several times a day.

Objective sleep quality can be measured at a much higher frequency as itdoes not necessarily require the person sleeping to be awake andrespond. While these samples can be performed on a daily basis, it iscontemplated that they would more likely be performed as frequent asseveral times a second or as much as once every 15 minutes or so to keepthe data collection to a reasonable level. The more rapid collection ofobjective sleep quality allows the sleep system to react more rapidly orinstantaneously to certain conditions if it is desired.

For example, the sleep system can monitor the objective sleep quality inreal-time during sleep and automatically adjust one or more aspects ofthe sleep system as soon as certain sleep conditions are detected. Ifduring sleep the person begins to wake or experience other changes insleep behavior the sleep system has the ability to both detect thiscondition and then automatically readjust the sleep system settings toput the person back to sleep or at least improve the immediate sleepcondition. Given the different sampling rate possibilities, it ispossible that a different number of samples would be used in thesubjective sleep quality measurement as in the objective sleep qualitymeasurement provided they have some correlation to each other based ontime or timing within a sleep cycle. For example, one or more subjectivesleep quality measurements taken in the past can be used and reused incombination with different objective sleep quality measurements takenmultiple times while a person is currently sleeping. Alternatively, thesleep system can be configured to match each subjective sleep qualitysample with a corresponding objective sleep quality sample taken at orabout the same time interval. The subjective sleep quality sample takenonce a day would be matched up with an objective sleep quality samplealso taken once a day at or about the same time interval.

The sleep system then correlates the sleep quality index and currentsleep system settings with historical sleep quality indices andcorresponding historical sleep system settings (510) and identifies atrend. By examining past sleep quality indices, the sleep system is ableto determine if a better group of settings would more likely or lesslikely to create a more effective environment for achieving certainsleep quality for the person. For example, a certain pattern of lightsor music may be effective at increasing a person's time to sleep and/ormay decrease the overall number of wakeups during sleep. Once asleep, adim light left on may help reduce the reoccurrence of wakeups or atleast reduce their effect and decrease the time to fall back to sleepafter a wakeup.

The sleep system modifies the sleep system settings depending on thecorrelation between the sleep quality index and the historical sleepquality indices in the system (512). If the proper correlation betweenthe current sleep quality index and the historical indices is discoveredthen the current sleep system settings are kept as the sleep systemsettings are already set to an optimal level (516). However, adivergence between the current sleep quality index and settings comparedwith the historical sleep quality indices and settings may indicate adifferent set of sleep system settings is more appropriate (512).Accordingly, implementations of the present invention would then modifythe sleep system settings based upon the historical sleep qualityindices, data and sleep system settings (514). For example, amodification may include changing the temperature of the environment andproviding a dim light during sleep to counteract wakeups or otherundesirable sleeping pattern or behavior. As previously described, thesleep system can make these changes as rapidly as the sampling rate forthe objective sleep quality measurements permit or can be fixed prior tosleeping and adjusted once a day after waking or on even a moreinfrequent basis.

Referring to FIG. 6, a set of alternate processes outline differentapproaches to gather historical sleep data, historical sleep qualityindices and historical sleep system settings in accordance with oneimplementation of the present invention. In a first case, a person usinga sleep system decides a threshold question of whether to access aglobal sleep repository containing sleep data for a larger population ofpeople (602). If a person wants to contribute, the person can decide tosubmit their own sleep and environment data gathered during sleep toglobal sleep repository (604). By contributing the sleep information,the data in the global sleep repository remains current and updated withthe latest information from the aggregate of people using theinformation.

Using this information in the global sleep repository, the sleep systemthen performs sleep trend analysis on global sleep repository thusupdating the various sleep quality indices & corresponding expectedsleep system settings (606). In practice, the sleep analysis isgenerally so complex and the data large that a separate sleep trendanalysis server 124 as depicted in FIG. 1 is required to incorporate thenewly contributed sleep data and recalculate the statistics for sleepsystem settings, objective and subjective sleep qualities as well asoverall sleep quality indices. Once the statistics are calculated, thesleep system accesses and mines the global sleep repository forsuggested sleep system settings in view of the person's sleep qualityindex and sleep goals (608). For example, the sleep system may discoverseveral different sleep system settings that seem appropriate but mustsomehow determine the most appropriate set of settings for the user bycarefully analyzing the sleep data, environmental data and sleep qualityindex.

In the alternate case, a person may decide not to access the globalsleep repository in which case the person instead contributes and usessleep and environment data gathered during sleep to local sleeprepository (610). The local sleep repository generally only includessleep data and environmental data concerning the particular person andhis or her corresponding sleep patterns. In some cases, this is moreeffective at suggesting sleep system settings as the results areinherently tailored to the individual. Of course, in other cases thereis a need for more solutions in order to solve a sleeping issue that maybe shared with many other people.

Next, the sleep system uses the local sleep repository information toperform sleep trend analysis and update sleep quality indices andcorresponding sleep system settings (612). These sleep system settingsand indices are much smaller and generally can be performed directlyusing the processing capabilities built into the sleep system. Todiscover the most optimal solution, the sleep system then mines thelocal sleep repository for suggested sleep system settings in view ofuser's sleep quality index and sleep goals (614).

The invention can be implemented in digital electronic circuitry, or incomputer hardware, firmware, software, or in combinations of them.Apparatus of the invention can be implemented in a computer programproduct tangibly embodied in a machine-readable storage device forexecution by a programmable processor; and method steps of the inventioncan be performed by a programmable processor executing a program ofinstructions to perform functions of the invention by operating on inputdata and generating output. The invention can be implementedadvantageously in one or more computer programs that are executable on aprogrammable system including at least one programmable processorcoupled to receive data and instructions from, and to transmit data andinstructions to, a data storage system, at least one input device, andat least one output device.

Each computer program can be implemented in a high-level procedural orobject-oriented programming language, or in assembly or machine languageif desired; and in any case, the language can be a compiled orinterpreted language. Suitable processors include, by way of example,both general and special purpose microprocessors. Generally, a processorwill receive instructions and data from a read-only memory and/or arandom access memory. Generally, a computer will include one or moremass storage devices for storing data files; such devices includemagnetic disks, such as internal hard disks and removable disks;magneto-optical disks; and optical disks. Storage devices suitable fortangibly embodying computer program instructions and data include allforms of non-volatile memory, including by way of example semiconductormemory devices, such as EPROM, EEPROM, and flash memory devices;magnetic disks such as internal hard disks and removable disks;magneto-optical disks; and CD-ROM disks. Any of the foregoing can besupplemented by, or incorporated in, ASICs (application-specificintegrated circuits).

To provide for interaction with a user, the invention can be implementedon a computer system having a display device such as a monitor or LCDscreen for displaying information to the user and a keyboard and apointing device such as a mouse or a trackball by which the user canprovide input to the computer system. The computer system can beprogrammed to provide a graphical user interface through which computerprograms interact with user.

Accordingly, the invention is not limited to the above-describedimplementations, but instead is defined by the appended claims in lightof their full scope of equivalents.

1. A sleep modification method comprising: gathering environmental dataand sleep data during a sleep by a person wherein the sleep data isuseful to generate an objective measure of sleep quality; creating asleep quality index from the objective measure of sleep quality;correlating the sleep quality index with a current set of sleep systemsettings wherein at least one sleep system setting affects at least oneaspect of an environment in the vicinity of the person; and modifyingthe current set of sleep system settings to obtain a desired sleepquality index.
 2. The method of claim 1 wherein gathering sleep datafrom the person and environmental data further includes contributing thesleep data and environmental data along with one or more correspondingsleep system settings into a sleep repository.
 3. The method of claim 2wherein the sleep repository further includes historical informationfrom the sleep of the person along with corresponding environmental datagathered over time from the environment associated with the person. 4.The method of claim 2 wherein the sleep repository further includeshaving historical sleep data from the sleep of the person as well ashistorical sleep data from one or more other people along withcorresponding environmental data gathered over time from the environmentassociated with the person and the one or more other people.
 5. Themethod of claim 1 wherein correlating the sleep quality index with acurrent set of sleep system settings further includes using at least onehistorical sleep quality index and corresponding historical sleep systemsettings.
 6. The method of claim 1 wherein the objective measure ofsleep quality includes one or more factors selected from a set offactors including: sleep inertia after waking up, sleep debtaccumulation, architecture of sleep phases, breathing quality, sleepefficiency, duration of wakeups during sleep time, actual frequency ofwakeups, sleep onset time, wake-up time, and total sleeping time andactual time taken to fall asleep.
 7. The method of claim 1 wherein thesleep quality index is a weighted combination of one or more objectivemeasures of sleep quality.
 8. The method of claim 5 wherein the at leastone historical sleep quality index and corresponding historical sleepsystem settings are derived from one or more previous sleep qualityindices and corresponding sleep system settings associated with theperson.
 9. The method of claim 5 wherein the at least one historicalsleep quality index and corresponding historical sleep system settingare derived from one or more previous sleep quality indices andcorresponding sleep system settings associated with the person incombination with previous sleep quality indices and corresponding sleepsystem settings associated one or more other people.
 10. The method ofclaim 1 wherein correlating the sleep quality index and the current setof sleep system settings further comprises: performing sleep trendanalysis on historical sleep data from the person and historicalenvironmental data to update the sleep quality index and one or moresleep system settings; and mining the historical sleep data and thehistorical environmental data for one or more suggested sleep systemsettings in view of desired sleep quality index and sleep goals for theperson.
 11. A sleep system for sleep analysis and modification,comprising: a set of one or more sleep repository databases having dataaccessible over a network and connected to one or more computer systems;a sleep trend analysis computer system that analyzes trends from thedata on the set of one or more sleep repository databases and generatessleep quality indices and corresponding expected sleep system settings;and a network that provides the expected sleep system settings to one ormore sleep systems for one or more people depending on each person'sgoals during sleep.
 12. The system of claim 11 wherein the set of one ormore sleep repository databases includes one or more datasets selectedfrom a set of datasets including: sleep data from one or more people,environmental data gathered during the sleep of one or more people, bodydata from one or more people, and one or more corresponding sleep systemsettings when modified affect the environment either before, during orafter a sleep.
 13. The system of claim 12 wherein each of the one ormore sleep systems have one or more body and sleep sensors capable ofgathering body data and sleep data from a person and one or moreenvironmental sensors capable of gathering environmental data eitherbefore, during or after a sleep by the person.
 14. The system of claim12 where each of the one or more sleep systems has one or more controlsfor altering an environment associated with a person wherein thecontrols are responsive to the one or more corresponding sleep systemsettings generated by the sleep trend analysis computer system.
 15. Asleep system comprising: a set of one or more sensors capable ofgathering sleep data from a person and environmental data either before,during or after a sleep by the person useful to generate an objectivemeasure of sleep quality; a processor capable of executing instructionsused in the analysis and control of the sleep of the person and theenvironment surrounding the person; a memory capable of holdinginstructions when executed generate an objective measure of sleepquality from the sleep data from the person along with gatheringenvironmental data during the sleep by the person, create a sleepquality index from the objective measure of sleep quality, correlate thesleep quality index and a current set of sleep system settings, modifythe current set of sleep system settings to obtain a desired sleepquality index; and a set of controls capable of changing one or moredifferent elements of an environment associated with the sleep systemand the current set of sleep system settings.
 16. The system of claim 15wherein the set of one or more sensors includes one or more sensorsselected from a set of sensors including: a respiration sensor, aheartbeat sensor, a movement sensor, an air sensor, a light sensor, asound sensor, a temperature sensor and other environment sensors. 17.The system of claim 15 wherein correlating the sleep quality index andthe current set of sleep system settings further includes using at leastone historical sleep quality index and corresponding historical sleepsystem settings.
 18. The system of claim 15 wherein the objectivemeasure of sleep quality includes one or more factors selected from aset of factors including: sleep inertia after waking up, sleep debtaccumulation, architecture of sleep phases, breathing quality, sleepefficiency, duration of wakeups during sleep time, actual frequency ofwakeups, sleep onset time, wake-up time, total sleeping time and actualtime taken to fall asleep.
 19. The system of claim 17 wherein the atleast one historical sleep quality index and corresponding historicalsleep system settings are derived from one or more previous sleepquality indices and corresponding sleep system settings associated withthe person.
 20. The system of claim 17 wherein the at least onehistorical sleep quality index and corresponding historical sleep systemsettings are derived from one or more previous sleep quality indices andcorresponding sleep system settings associated with the person incombination with previous sleep quality indices and corresponding sleepsystem settings associated one or more other people.
 21. The system ofclaim 15 wherein the instructions that correlate the sleep quality indexand the current set of sleep system settings further compriseinstructions that: perform sleep trend analysis on historical sleep datafrom the person and historical environmental data to update the sleepquality index and one or more sleep system settings; and mine thehistorical sleep data and the historical environmental data for one ormore suggested sleep system settings in view of desired sleep qualityindex and sleep goals for the person.
 22. The system of claim 15 whereinthe one or more different elements of the environment are selected froma set of different elements including: light, temperature, air, soundand vibration.